Energy Storage System Research Articles

Recent progress of ion-doping methods in modifying layered oxide cathode materials for sodium-ion batteries

Typically, the cathode materials contribute the most in achieving the commercialization of sodium-ion batteries (SIBs) as the cathodes take up the most proportion of the full cells cost. Hence, developing cathode materials with a high specific capacity, perfect capacity retention, long cycling lifetime, and strong chemical/environmental stability is of undoubted importance. Researchers are now using many methodologies to improve the performance of different types of cathodes. Among all these, ion-doping used in modifying layered oxide (NaxTMO2, in which TM=transition metal; 0<x≤1) cathode materials seem to be one of the most popular methods. This is because that the NaxTMO2 cathodes offer perfect energy density and Na+ conductivity, while ion-doping methods could help mitigate the phase transition, sluggish kinetics, and air instability challenges. As a result, this review summarizes the recent progress of ion-doped NaxTMO2 cathodes modification strategies, divided into three parts in dealing with the above three challenges respectively. This work targets for facilitating the development of ion-doping methods used in commercial NaxTMO2 modification and pave the way for the next generation of energy storage systems.

Optimizing EV fast charging infrastructure: integrating high-gain interleaved converter with advanced MPPT

ABSTRACT Modernizing the Electric Vehicle (EV) charging infrastructure is essential for the widespread adoption of electric mobility. This research addresses the imperative need for enhancing the power performance of photovoltaic (PV) grid-connected inverters for EV fast charging applications. The system integrates Voltage-Oriented Control (VOC) for the PV inverter, a High-Gain Interleaved (Single Ended Primary Inductance Converter) SEPIC-Cuk (HGISC) converter, and a Bald Eagle Search Optimized Adaptive Neuro Fuzzy Inference System (BESO-ANFIS)) algorithm. VOC with Proportional Resonant (PR) ensures optimized energy transfer to grid, while the HGIBC converter enhances power performance. The proposed BESO-ANFIS Maximum Power Point Tracking (MPPT) dynamically tracks the PV array’s Maximum Power Point (MPP) under varying conditions. Additionally, a bidirectional battery converter in the energy storage system optimizes power usage. The synergistic implementation of these advanced controller results in a comprehensive solution, showcasing improved power output, grid integration, and efficient solar energy utilization for EV fast charging. MATLAB simulations and experiments demonstrate 97% efficiency and reduced Total Harmonic Distortion (THD) of 0.98%, positioning this research as an advanced solution for EV charging infrastructure enhancement.

Optimal operating strategy of hybrid heat pump − boiler systems with photovoltaics and battery storage

The growing need to reduce energy consumption and greenhouse gas emissions is driving the search for more efficient heating solutions in buildings. Hybrid heating systems, which combine air-to-water heat pumps (AWHP) with traditional gas boilers, are a common solution after refurbishment investments. However, managing these systems effectively, particularly when integrated with photovoltaic (PV) panels and battery energy storage systems (BESS), remains a complex task. For instance, heat pumps perform poorly in very cold conditions, making boilers a more efficient option; however, it might be advantageous to use it to increase electricity self-consumption. Optimal management depends on multiple factors, including future forecast data. In this paper, a daily optimization program is developed by means of a brute-force approach using forecast data. The core innovation of this paper is the use of an artificial neural network (ANN) that, trained on predictive optimization results, can determine the optimal solution in real-time without the need for future forecasts. The ANN achieved a 99.16% accuracy in new scenarios, successfully optimizing costs, CO2 emissions, and primary energy use. Results indicate up to 19% cost savings in colder cities, a 12% reduction in CO2 emissions, and a 3% decrease in primary energy consumption. This approach holds significant potential for enhancing the integration of renewable energy sources, contributing to long-term sustainability goals.

Dual-Steric Hindrance Modulation of Interface Electrochemistry for Potassium-Ion Batteries.

Electrolyte chemistry regulation is a feasible and effective approach to achieving a stable electrode-electrolyte interface. How to realize such regulation and establish the relationship between the liquid-phase electrolyte environment and solid-phase electrode remains a significant challenge, especially in solid electrolyte interphase (SEI) for metal-ion batteries. In this work, solvent/anion steric hindrance is regarded as an essential factor in exploring the electrolyte chemistry regulation on forming ether-based K+-dominated SEI interface through the cross-combination strategy. Theoretical calculation and experimental evidence have successfully indicated a general principle that the combination of increasing solvent steric hindrance with decreasing anion steric hindrance indeed prompts the construction of an ideal anion-rich sheath solvation structure and guarantees the cycling stability of antimony-based alloy electrode (Sb@3DC, Sb nanoparticles anchored in three-dimensional carbon). These confirm the critical role of electrolyte modulation based on molecular design in the formation of stable solid-liquid interfaces, particularly in electrochemical energy storage systems.

Sn Penetrated Zincophilic Interface Design in Porous Zn Substrate for High Performance Zn-Ion Battery.

Rechargeable zinc-ion batteries are considered an ideal energy storage system due to their low cost and nonflammable aqueous electrolyte. However, dendrite growth, hydrogen evolution reaction, and self-corrosion of zinc anode brought about serious safety risks including short circuits and electrode expansion. Therefore, a modified host-design strategy with a 3D porous structure and bulk-phase penetrated zincophilic interface is proposed to boost the stability and lifetime of the Zn anode. The porous Zn substrate is constructed by universal HCl etching and the uniform and tight Sn-penetrated zincophilic interface is formed by effective electron beam evaporation (EBE). The porous substrate can uniform zinc ion flux and the Sn coating could effectively improve zinc ion deposition behavior, thus inhibiting the risk of dendrites growth and side reaction. As a result, the 3D Zn substrate with Sn interface (3D Zn@Sn) exhibits prolonged galvanostatic cycling performance up to 4500h with a low polarization of ≈25mV (1mAcm-2, 1mAhcm-2) in the symmetric cell. The full cell assembled with KVOH@Ti could maintain a high specific capacity of 148.6mAhg-1 after 500 galvanostatic cycles (10Ag-1). This work proposed an improved electrode design to realize the high performance of zinc ion batteries.

Origin of the High Catalytic Activity of MoS2 in Na-S Batteries: Electrochemically Reconstructed Mo Single Atoms.

Room-temperature sodium-sulfur (RT Na-S) batteries with high energy density and low cost are considered promising next-generation electrochemical energy storage systems. However, their practical feasibility is seriously impeded by the shuttle effect of sodium polysulfide (NaPSs) resulting from the sluggish reaction kinetics. Introducing a suitable catalyst to accelerate conversion of NaPSs is the most used strategy to inhibit the shuttle effect. Traditional catalytic approaches often want to avoid the irreversible phase transition of the catalyst at a deep discharge. On the contrary, here, we leverage the intrinsic structural tunability of the MoS2 catalyst in the opposite direction and innovatively propose a voltage modulation strategy for in situ generation of trace Mo single atoms (MoSAC) during the first charge-discharge process, leading to the formation of highly active catalytic phases (MoS2/MoSAC) through the self-reconstruction. Theoretical calculations reveal that the incorporation of MoSAC modulates the electronic structure of the Mo d-band center, which not only effectively promotes the d-p orbital hybridization but also accelerates the catalytic intermediate desorption by the bonding transition, the dynamic single-atom synergistic catalytic mechanism enhances the adsorption response between the metal active site and NaPSs, which significantly improves the sulfur redox reaction (SRR), and the initial capacity of the MoS2/MoSAC/CF@S cell at 0.2 A g-1 is increased by 46.58% compared to that of the MoS2/CF@S cell. The discovery of the MoS2/MoSAC/CF catalyst provides new insights into adjusting the structure and function of transition metal disulfide catalysts at the atomic scale, offering hope for the development of high-specific-energy RT Na-S batteries.

Hazardous Effects of Battery Waste and Role of the Battery Waste Management Rule 2022 in Enhancing Energy Efficiency

Replacing batteries in present world is challenging because they are extensively utilised in every facet of human existence. These batteries contain a variety of toxic heavy metals, including as cadmium, copper, lead, mercury, nickel, and zinc, all of which pose risks to human health and the environment. Improperly disposing of used batteries in landfills leads to the infiltration of toxic heavy metals and other dangerous compounds into the soil and water over time. India’s long-term development has significant challenges in both reducing CO2 emissions and meeting the energy demands of its large population. This has significantly bolstered the electric vehicle (EV) and renewable energy industries. Battery-based energy storage systems can enhance the management of operational and energy evacuation challenges associated with renewable energy. Consequently, the effective disposal of battery waste is more crucial than battery production. However, it is neglected often, specially in developing and impoverished nations. Three established methods exist for preventing and managing the issues arising from the inappropriate disposal of used batteries. The three R’s are: decrease, replenish, and reuse. This article initially analyses the health and environmental consequences of battery waste, and subsequently highlights the potential of new regulations on battery waste management to effectively handle huge amounts of battery waste and encourage energy conservation.

Multi-objective optimal configuration of CCHP system containing hybrid electric-hydrogen energy storage system

In order to cope with the increasing energy demand and achieve the “double carbon “goal of China’s 14th Five-Year Plan,” combined with hydrogen energy storage technology, it has the characteristics of zero pollution, high efficiency and rich source. In the context of reducing energy consumption and the vigorous development of hydrogen energy storage technology, a multi-objective optimization configuration model with economy, energy consumption index and carbon emission index is proposed, which takes into account the working characteristics of the hydrogen energy storage system, and the exothermic heat release from the electrolysis tanks and fuel cells when they are working to provide the loads with an additional heat source of the Combined Cooling, Heating and Power (CCHP) system, to reduce energy consumption and carbon emission. Finally, taking a region as an example, a multi-objective optimization algorithm based on decomposition is used to solve the model, so as to obtain a series of alternatives with better optimization effect. At the same time, the two-way projection method based on interval intuitionistic fuzzy information is used to make decisions, and the scheme that optimizes the economy, energy consumption index and carbon emission index is obtained, which verifies the feasibility of the system proposed in this paper.

Poly(ionic) Liquid-Enhanced Ion Dynamics in Cellulose-Derived Gel Polymer Electrolytes.

Gel polymer electrolytes (GPEs) are regarded as a promising alternative to conventional electrolytes, combining the advantages of solid and liquid electrolytes. Leveraging the abundance and eco-friendliness of cellulose-based materials, GPEs were produced using methyl cellulose and incorporating various doping agents, either an ionic liquid (1-Butyl-1-methylpyrrolidinium bis(trifluoromethylsulfonyl)imide [Pyr14][TFSI]), its polymeric ionic liquid analogue (Poly(diallyldimethylammonium bis(trifluoromethylsulfonyl)imide) [PDADMA][TFSI]), or an anionically charged backbone polymeric ionic liquid (lithium poly[(4-styrenesulfonyl)(trifluoromethyl(S-trifluoromethylsulfonylimino) sulfonyl) imide] LiP[STFSI]). The ion dynamics and molecular interactions within the GPEs were thoroughly analyzed using Attenuated Total Reflectance Fourier-Transform Infrared Spectroscopy (ATR-FTIR), Heteronuclear Overhauser Enhancement Spectroscopy (HOESY), and Pulsed-Field Gradient Nuclear Magnetic Resonance Diffusion (PFG-NMR). Li+ transference numbers (tLi+) were successfully calculated. Our study found that by combining slow-diffusing polymeric ionic liquids (PILs) with fast-diffusing lithium salt, we were able to achieve transference numbers comparable to those of liquid electrolytes, especially with the anionic PIL, LiP[STFSI]. This research highlights the influence of the polymer's nature on lithium-ion transport within GPEs. Additionally, micro supercapacitor (MSC) devices assembled with these GPEs exhibited capacitive behavior. These findings suggest that further optimization of GPE composition could significantly improve their performance, thereby positioning them for application in sustainable and efficient energy storage systems.

Research on Energy Management Technology of Photovoltaic-FESS-EV Load Microgrid System

This study focuses on the development and implementation of coordinated control and energy management strategies for a photovoltaic–flywheel energy storage system (PV-FESS)-electric vehicle (EV) load microgrid with direct current (DC). A comprehensive PV-FESS microgrid system is constructed, comprising PV power generation, a flywheel energy storage array, and electric vehicle loads. The research delves into the control strategies for each subsystem within the microgrid, investigating both steady-state operations and transitions between different states. A novel energy management strategy, centered on event-driven mode switching, is proposed to ensure the coordinated control and stable operation of the entire system. Based on the simulation results, the PV system cannot cope with the load demand power when it is increased to a maximum of 2800 W, the effectiveness of the individual control strategies, the coordinated control of the subsystems, and the overall energy management approach are confirmed. The main contribution of this research is the development of a coordinated control mechanism that integrates PV generation with FESS and EV loads, ensuring synchronized operation and enhanced stability of the microgrid. This work provides significant insights into optimizing energy distribution and minimizing losses within microgrid systems, thereby advancing the field of energy management in DC microgrids.

Robust Distributed Load Frequency Control for Multi-Area Power Systems with Photovoltaic and Battery Energy Storage System

The intermittent power generation of renewable energy sources (RESs) interrupts the balance between power generation and demand load due to the increased frequency fluctuation, which challenges the frequency stability analysis and control synthesis of power generation systems. This paper proposes a robust distributed load frequency control (DLFC) scheme for multi-area power systems. Firstly, a multi-area power system is constructed by integrating photovoltaic (PV) and battery energy storage systems (BESSs). Then, by employing the linear matrix inequality (LMI) technique, the sufficient condition capable of ensuring that the proposed controller satisfies H∞ robust performance in the sense of asymptotic stability is derived. Finally, testing is conducted on a four-area renewable power system, and results verify the strong robustness of the proposed controller against load disturbance and intermittence of RESs.

Renewable Solar Energy Facilities in South America—The Road to a Low-Carbon Sustainable Energy Matrix: A Systematic Review

South America is a place on the planet that stands out with enormous potential linked to renewable energies. Countries in this region have developed private investment projects to carry out an energy transition from fossil energies to clean energies and contribute to climate change mitigation. The sun resource is one of the more abundant sources of renewable energies that stands out in South America, especially in the Atacama Desert. In this context, South American countries are developing sustainable actions/strategies linked to implementing solar photovoltaic (PV) and concentrated solar power (CSP) facilities and achieving carbon neutrality for the year 2050. As a result, this systematic review presents the progress, new trends, and the road to a sustainable paradigm with disruptive innovations like artificial intelligence, robots, and unmanned aerial vehicles (UAVs) for solar energy facilities in the region. According to the findings, solar energy infrastructure was applied in South America during the global climate change crisis era. Different levels of implementation in solar photovoltaic (PV) facilities have been reached in each country, with the region being a worldwide research and development (R&D) hotspot. Also, high potential exists for concentrated solar power (CSP) facilities considering the technology evolution, and for the implementation of the hybridization of solar photovoltaic (PV) facilities with onshore wind farm infrastructures, decreasing the capital/operation costs of the projects. Finally, synergy between solar energy infrastructures with emerging technologies linked with low-carbon economies like battery energy storage systems (BESSs) and the use of floating solar PV plants looks like a promising sustainable solution.

N, F Co-Doped Carbon Material Self-Supporting Cathode for High-Performance Lithium-Oxygen Batteries.

The Li-O2 battery has emerged as a promising energy storage system due to its exceptionally high theoretical energy density of 3500 Wh kg-1. However, the sluggish kinetics associated with the formation and decomposition of discharge product Li2O2 poses several challenges in Li-O2 batteries, including excessive over-potential, limited rate performance, and reduced actual specific energy. Consequently, the development of cost-effective cathode catalysts with enhanced catalytic activity and long-term stability represents a viable approach to address these challenges. In this study, commercial melamine foam is utilized as a precursor material which was subjected to pyrolysis at elevated temperatures with PVDF to synthesize N, F co-doped self-supporting carbon cathode (NF-NSC). Remarkably, thanks to the synergistic effects of N, F heteroatomic in conjunction with the inherent three-dimensional reticular porous structure, NF-NSC exhibited enhanced electrochemical performance when utilized in Li-O2 batteries. Specifically, the NF-NSC cathode demonstrated an impressive discharge specific capacity of up to 35204 mAh g-1 alongside a low over-potential (0.86 V) and excellent cycling stability (146 cycles).

Study on two‐stage optimal scheduling of DC distribution networks considering flexible load response

AbstractDue to the aim of developing sustainable energy systems, promoting the large‐scale accommodation of distributed renewable energy sources (DRESs) and flexible loads in DC distribution networks (DCDNs) is significant. The uncertainty of DRESs and the insufficient use of flexible loads pose a considerable challenge to the economical and safe operation of DCDNs. To address the challenge, this paper puts forward a two‐stage optimal scheduling model for the DCDNs considering flexible load response. The proposed model realises joint economic optimisation and reactive power optimisation, which is solved by the hybrid NSGAII‐MOPSO algorithm and the CPLEX. The performance of the proposed model in the modified Institute of Electrical and Electronics Engineers 33‐node system with the DCDNs is validated under different scenarios. The hybrid NSGAII‐MOPSO performs better in obtaining the Pareto front than the NSGA‐II and MOPSO individually. Compared to the traditional scheduling model, the proposed model can realise the power coordination of the flexible loads and energy storage systems to reduce the negative impact of uncertainty of DRESs while decreasing operating costs and carbon emissions by 3.94% and 36.4%. In addition, the proposed model can alleviate the network losses and ensure the node voltage for the DCDNs. Hence, the efficiency of the proposed model has been confirmed.

Energy Storage Solutions to De-Carbonize the Electric Supply in Jordan

This paper aims to estimate the size of Energy Storage Systems (ESS) required de-carbonizing the electrical network in Jordan. Load profile in addition to the PV and Wind energy profiles were studied and used as input data to the simulation model. Different cases of RE penetration levels as a percentage of load demand were considered and entered to the simulation model as well. Other factors, such as allowed over-generation and ESS efficiency also provided and calculations carried out accordingly. In addition to the technical consideration, an economic analysis approach added to the study. Results show that staying with the current level of RE penetrations, i.e. at PV 11% and W 9% (RE level 20% of load demand) and 5% curtailment, no need to install ESS to absorb the RE intermittency and variability. As RE penetration level increases, the need for ESS becomes necessary, i.e. to reach 100% RE penetration and de-carbonize the electrical network accordingly, an ESS of 138,900.00MWH/ 7,386.57MW PHES would be required at PV 65% and Wind 35% penetration level and 25% curtailment with initial CAPEX investment of JOD 15,367,314,444.10. Economic feasibility study shows that with the current RE energy prices and ESS CAPEX, reaching the 100% RE penetration level would not be the optimum solution as there will be a negative cost impact, unless these prices reduced to a certain level making the solution feasible.

Discrete control model Q-learning for an energy storage system with a hydrogen unit of an autonomous hybrid power plant of a railway substation

The paper considers the prospects for creating autonomous hybrid power plants using renewable energy sources and hydrogen as energy storage systems, as well as storage batteries, for the railway power supply system. A comparative analysis of various energy storage systems is carried out. A simulation model has been created that takes into account the characteristics of electric rolling stock trains, a model of the contact network of the inter-station zone of the railway stage, and a model of the energy storage system. Managing the flow of electricity in an autonomous hybrid power plant requires considering forecasts of electricity consumption and generation and the level of charge of the energy storage device. To solve the problem of synthesizing a control algorithm, the use of matrix Q-learning is proposed. The novelty of the study lies in the proposed approach of applying Q-learning to the problem under consideration based on discretization of input and output parameters of the model and verification of the approach on a simulation model built for a real railway section between the Yaya and Izhmorskaya stations (Kemerovo region of the Russian Federation). It is shown that the use of the proposed system makes it possible to equalize the voltage in the network between traction substations and provide a significant increase in the capacity of the railway section, and the proposed method of matrix Q-learning makes it possible to synthesize an effective algorithm for controlling the energy storage system as part of an autonomous hybrid power plant.

Optimal expansion planning of a self-healing distribution system considering resiliency investment alternatives

This paper proposes a three-stage optimization framework for the expansion planning of a self-healing distribution system that determines the optimal characteristics of distributed generation, energy storage systems, electric vehicle charging stations, and sectionalizing switches for the planning horizon. The main contribution of this model is that the proposed model considers the resilient investment alternatives in the expansion planning exercise to reduce the system's vulnerability against external shocks. The mobile energy storage system commitment in contingent conditions is another contribution of this paper. In the first stage, the optimal location, capacity, and time of installation of the electricity facilities are calculated. Then, the optimal allocation of sectionalizing switches is performed in the second stage. The third stage consists of three levels. In the first and second levels, the optimal normal and contingent operational scheduling are determined, respectively. The system is sectionalized into multi-microgrid systems in contingent conditions. Finally, the resilient investment alternatives for the designed system are evaluated. The proposed model utilizes a self-healing index and resilient expansion planning index to assess the impacts of resilient investment alternatives on the operational scheduling conditions. The proposed model was evaluated using the IEEE 123-bus system. The proposed method reduced the estimated average value of the worst-case energy not supplied by 50.52 % for the 5th year of the planning horizon concerning the no-resiliency investment case. Further, the proposed resilience investment method increased the self-healing index by about 9.32 % concerning the no-resiliency investment case.

3D-Printed Polymeric Biomaterials for Health Applications.

3D printing, also known as additive manufacturing, holds immense potential for rapid prototyping and customized production of functional health-related devices. With advancements in polymer chemistry and biomedical engineering, polymeric biomaterials have become integral to 3D-printed biomedical applications. However, there still exists a bottleneck in the compatibility of polymeric biomaterials with different 3D printing methods, as well as intrinsic challenges such as limited printing resolution and rates. Therefore, this review aims to introduce the current state-of-the-art in 3D-printed functional polymeric health-related devices. It begins with an overview of the landscape of 3D printing techniques, followed by an examination of commonly used polymeric biomaterials. Subsequently, examples of 3D-printed biomedical devices are provided and classified into categories such as biosensors, bioactuators, soft robotics, energy storage systems, self-powered devices, and data science in bioplotting. The emphasis is on exploring the current capabilities of 3D printing in manufacturing polymeric biomaterials into desired geometries that facilitate device functionality and studying the reasons for material choice. Finally, an outlook with challenges and possible improvements in the near future is presented, projecting the contribution of general 3D printing and polymeric biomaterials in the field of healthcare.

A Deep Learning Dependent Controller for Advanced Ultracapacitor SoC Concept to Increase Battery Life Span of Electric Vehicles

ABSTRACTOn a global scale, significant progress is being made in the field of battery technology for Electric Vehicle (EV) applications, driven by the need to combat carbon emissions and mitigate the effects of global warming. Accurately determining critical parameters, making sure battery storage system diagnosis, and functioning are correct are critical to the feasibility of EVs. However, insufficient supervision and safety measures for these storage systems may lead to serious problems like a thermal runaway, overcharging, overheating, cell imbalances, and fire hazards. To tackle these challenges, the presence of an efficient battery management system becomes paramount. By facilitating accurate monitoring, managing heat dissipation, regulating charging‐discharging procedures, guaranteeing battery safety, and offering protection measures, this system is essential to maximizing battery performance. The key intention of this innovative approach is to improve the longevity of EV batteries during extended periods of operation. By assessing vehicle velocity, remaining battery energy, and State of Charge (SoC), the proposed method effectively manages SoC in both the battery and ultracapacitor. This control is accomplished through a two‐stage convolutional neural network‐based system known as the Charge Sustain‐CNN Controller and the Charge Deplete‐CNN Controller. These controllers are fine‐tuned using the Fractional Latrans‐Hunt optimization (FLHO) algorithm to optimize the performance. The evaluation criteria encompass the battery and ultracapacitor's energy efficiency, as well as vehicle velocity. This novel approach significantly improves the energy storage system in EVs, leading to enhanced energy efficiency and prolonged battery life. Ultimately, experimental results validate the practicality and effectiveness of this developed method. Specifically, the proposed approach attained the Battery's SoC of 72.47%, 91.99%, and 82.88% for the different drive cycles including the FTP75, J1015, and UDDS, respectively.

Electrostatic Shielding Engineering for Stable Zn Metal Anodes

AbstractAqueous Zn‐ion batteries (AZIBs) are promising energy storage systems due to their low cost, excellent safety, and environmental friendliness. However, challenges like uncontrollable dendrite growth and side reactions during battery operation limit their commercialization. Addressing these issues requires regulating ion deposition behavior at the anode/electrolyte interface. The electrostatic shielding effect, which leverages the interplay between electric potential and ionic motion, provides a unique mechanism to inhibit zinc dendrites and side reactions effectively. Despite significant progress in understanding electrostatic shielding in AZIBs, a comprehensive summary of its effects is still lacking. This paper first reviews the primary challenges in AZIBs and then describes how the electrostatic shielding effect can optimize their performance. Existing strategies for achieving electrostatic shielding through anode structure optimization and electrolyte optimization‐are classified and analyzed. Finally, the review summarizes current electrostatic shielding strategies for stabilizing zinc anodes, identifies existing challenges, and discusses the future potential, and for this approach in AZIBs.